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Record W1963925180 · doi:10.1159/000161058

Cortical Serotonin 1A Receptor Levels Are Associated with Depression in Patients with Dementia with Lewy Bodies and Parkinson’s Disease Dementia

2008· article· en· W1963925180 on OpenAlexaff
Sally I. Sharp, Clive Ballard, Iryna Ziabreva, Margaret A. Piggott, Robert H. Perry, Elaine K. Perry, Dag Aarsland, Uwe Ehrt, Jan Larsen, Paul T. Francis

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsCentre for Movement Disorders
FundersMedical Research CouncilNorges ForskningsrådUniversitetet i Bergen
KeywordsDementia with Lewy bodiesDementiaInternal medicinePsychologyEndocrinologyParkinson's diseaseDepression (economics)Alzheimer's diseaseMedicineDisease

Abstract

fetched live from OpenAlex

<i>Background:</i> Serotonin 1A receptors (5-HT<sub>1A</sub>) have not been studied in dementia with Lewy bodies (DLB) or Parkinson’s disease dementia (PDD) patients with depression. <i>Aim:</i> To examine 5-HT<sub>1A</sub> in DLB and PDD postmortem in relation to depression. <i>Methods:</i> [<sup>3</sup>H]8-hydroxy-2-dipropylaminotetralin binding to 5-HT<sub>1A</sub> was determined in temporal cortex (Brodmann areas, BA20 and BA36) from 10 DLB patients, 17 PDD patients and 9 controls. <i>Results:</i> 5-HT<sub>1A</sub> density was significantly higher in BA36 in combined DLB/PDD patients with depression, but was unaltered in BA20. <i>Conclusion: </i>Higher BA36 5-HT<sub>1A</sub> density in PDD and DLB patients than in control is dependent on whether the patient had experienced depression during life, not DLB/PDD diagnosis. A 5-HT<sub>1A</sub> antagonist adjuvant may improve treatment of depression in dementia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.230
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2008
Admission routes1
Has abstractyes

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